Pengenalan Bahasa Isyarat Indonesia menggunakan Mediapipe dengan Model Random Forest dan Multinomial Logistic Regression

Imam Suyudi (Universitas Gadjah Mada, Daerah Istimewa Yogyakarta)
Sudadio Sudadio (Universitas Gadjah Mada, Daerah Istimewa Yogyakarta)
Suherman Suherman (Universitas Gadjah Mada, Daerah Istimewa Yogyakarta)

Jurnal Ilmu Siber dan Teknologi Digital
Vol. 1 No. 1 (2022): November

Purpose: This research aims to create a random forest machine learning model and logistic regression that can perform the sign language recognition of the Indonesian Sign Language System (SIBI) using a regular RGB camera with the MediaPipe framework. Research methodology: Both variables in this study are measured using Innovative Work Behavior (IWB) Scale from Janssen (2000) and Connor-Davidson Resilience Scale (CD-RISC) from Connor & Davidson (2003) that was distributed through Google Form link. The data analysis is done with the support of the 25th version of SPSS (Statistical Package for Social Science). Results: Resilience has a significant correlation with innovative work behavior among college students. Limitations: No strict controls of questionnaire administration, the questionnaire consists of 6 different measurements from the research team, and can't be fully generalized to the college students population. Contribution: New findings of correlation between two variables among new samples.